Use the linear regression model yˆ=−24.8x+564.38 to predict the y-value for x=63.

The volume (in cubic feet) of a black cherry tree can be modeled by the equation y = - 50.7 + 0.3x, + 5.2x2, where x, is the tree's height (in feet) and x2 is the tree's diameter (in inches). Use the multiple regression equation to predict the y-values for the values of the independent variables. X1 = 70, x, = 8.9 The predicted volume is cubic feet. (Round to one decimal place as needed.)

The equation used to predict annual cauliflower yield (in pounds per acre) is y = 24,121 +4.505x₁ -4.772x₂, where x₁ is the number of acres planted and x2 is the number of acres harvested. Use the multiple regression equation to predict the y-values for the values of the independent variables. (a) x₁ =35,100, x₂ =35,500 (b) x₁ = 36,800, X2=37,100 (c) x₁ = 37,900, x₂ = 38,000 (d) x₁ =41,100, x₂ = 41,200 (a) The predicted yield is pounds per acre. (Round to one decimal place as needed.) (b) The predicted yield is pounds per acre. (Round to one decimal place as needed.) (c) The predicted yield is pounds per acre. (Round to one decimal place as needed.) (d) The predicted yield is pounds per acre (Round to one decimal place as needed.)

X₁ is the The volume (in cubic feet) of a black cherry tree can be modeled by the equation y = -51.2 +0.4x₁ + 4.8x2, where tree's height (in feet) and x₂ is the tree's diameter (in inches). Use the multiple regression equation to predict the y-values for the values of the independent variables. (a) x₁ = 73, x₂ = 8.8 (b) x₁ = 67, x₂ = 11.5 (c) x₁ = 85, x₂ = 17.6 (d) x₁ = 92, x₂ = 20.8 cubic feet. (a) The predicted volume is (Round to one decimal place as needed.) (b) The predicted volume is cubic feet. (Round to one decimal place as needed.) (c) The predicted volume is cubic feet. (Round to one decimal place as needed.) (d) The predicted volume is cubic feet. (Round to one decimal place as needed.) Next

The y-intercept in a linear regression model is always relevant and of interest to investigators for every model constructed.  True  False

The equation used to predict annual cauliflower yield (in pounds per acre) is y =24,231 + 4.417x, - 4.677x,, where x, is the number of acres planted and x, is the number of acres harvested. Use the multiple regression equation to predict the y-values for the values of the independent variables. (a) x, = 36,100, X2 = 36,500 (b) x, = 37,800, X2 = 38,100 (c) X4 = 38,800, X2 = 39,000 (d) x, = 42,100, X2 = 42,200 %3D %3D (a) The predicted yield is pounds per acre. (Round to one decimal place as needed.)

A high school wants to predict her students' score on a midterm exam y, given the number of hours a student spent studying x1 and the student's average homework grade x2. She obtains the multiple regression equation yˆ=−2.662+4.686x1+0.753x2. Predict the midterm exam score of a student with an average homework grade of 90, who spent 5 hours studying, rounding to the nearest integer.

Use the linear regression model yˆ=−21.9x+927.93 to predict the y-value for x=37.

The volume​ (in cubic​ feet) of a black cherry tree can be modeled by the equation y=−50.8+0.3x1+5.1x2​, where x1 is the​ tree's height​ (in feet) and x2 is the​ tree's diameter​ (in inches). Use the multiple regression equation to predict the​ y-values for the values of the independent variables.

The volume​ (in cubic​ feet) of a black cherry tree can be modeled by the equation y=−51.9+0.3x1+4.9x2​, where x1 is the​ tree's height​ (in feet) and x2 is the​ tree's diameter​ (in inches). Use the multiple regression equation to predict the​ y-values for the values of the independent variables.